The long-term objective of this project is to develop a capability of computer-based analysis and reporting of clinical EEGs. Separate approaches are planned for EEG background activity, and for brief transients (spikes, spike-wave activity, sharp waves), respectively. Work to date has primarily focussed on the use of adaptive segmentation as a method of analysis of ongoing EEG activity (i.e., exclusive of brief transients), a method which has the advantage of automatic segmentation and clustering, with the provision of summry descriptors, for each type of ongoing activity, in the event that there are different types of ongoing activity (e.g., intermittent slow-waves and a normal background). In the next year, work with adaptive segmentation will continue, with particular emphasis on the application of this technique to EEG recordings in which there are prominent changes in the background (e.g., records from monitoring of carotid endarterectomies). An important part of this project is the minimization or elimination of artifact, in EEG recordings. In an earlier project, EKG artifact minimization was accomplished. In the present period, artifact from eye movement and from muscle tension (EMG) have been the focus of attention, and methodologies appropriate to each of these to problems separately have been evolved, and are undergoing tests. In the next period, also, some preliminary work concerning the use of simplified methods of spike/sharp wave detection will be undertaken, as an alternative to more complex computer-based methods which have previously been developed by this and by other investigators.